1. Field of the Invention
The present invention relates to an object recognition device and an object recognition method for recognition of an object that exists in an image. Furthermore, the invention relates to an object recognition program executed by an object recognition device for recognition of an object that exists in an image. In addition, the invention relates to a feature registration device and a feature registration method used in an object recognition device for recognition of an object that exists in an image. Moreover, the invention relates to a feature registration program executed by a feature registration device.
2. Description of the Related Art
Studies have long been made on recognition of an object that exists in an image acquired from a camera. In a major existing method, an object is described globally, i.e., a template of textures of the entire object is prepared, and recognition is carried out through matching in which the template is applied to the entire object. In this method, however, it is desired that the whole of the object is visible because it is very difficult for this method to address e.g. partial hiding and rotation of an object in the acquired image.
However, in recent years, there have been successfully proposed methods that are very robust against partial hiding, rotation and so on of an object in an acquired image. In these methods, an object is described with local features and matching between the local features is carried out. The documents of these methods are typified by D. G. Lowe, “Object Recognition from local scale-invariant features”, ICCV, 1999. However, although this method is very effective for an object having a large number of textures, it is difficult to apply this method to an object having a small number of textures.
As for recognition of an object having a small number of textures, there have been proposed many methods in which the outline shape of an object, i.e., the edge information of the object, is used. A global description scheme has been mainly employed also in these recognition methods using edge information. However, it is very difficult for the global description scheme to extract the outline of an entire object in a general image, and this scheme involves a problem of being fragile against partial hiding as described above. In recent years, however, following the success in the above-described description methods with texture-based local features, there have been proposed methods in which edge information is locally described. Examples of documents of the methods are as follows: S. Belongie, J. Malik, J. Puzicha, “Shape Matching and Object Recognition Using Shape Contexts”, PAMI, 2002; and F. Jurie and C. Schmidr “Scale-invariant shape features for recognition of object categories”, CVPR, 2004.